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Book of Abstracts for ESGI 188 now available

The 188th European Study Group with Industry (ESGI 188), hosted from May 26 to 30 at Bilbao's B Accelerator Tower (BAT), has concluded with the release of its Book of Abstracts. This event, organized by the Basque Center for Applied Mathematics (BCAM) in collaboration with the Bizkaia Provincial…

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Researchers from BCAM, ARAYA INC., The University Of Sussex, and The University Of Kyoto develop a new class of Artificial Intelligence models called CURVED NEURAL NETWORKS

  •  What if Artificial Intelligence could remember things not just well, but faster or more reliably?

BCAM people

BCAM’s postdoctoral researcher Verónica Álvarez Castro, awarded as one of the Young Researchers in Computer Science in the The Research Awards of the Scientific Society of Computer Science of Spain (SCIE )-Fundación BBVA

  • The jury of these awards has taken into account her contributions to machine learning in the field of adaptation to temporal changes, both in its mo

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EKIOCEAN concludes two years of research into sustainable solutions for floating marine photovoltaics

EKIOCEAN Project Concludes Two Years of Research on Sustainable Solutions for Floating Marine Photovoltaics

Latest publications

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Efficient Localization via Soft Information With Generic Sensing Measurements

Bartoletti, S.; Mazuelas, S.; Conti, A.; Win, M. (2025-06-05)

Accurate location awareness is essential for various context-based applications. This calls for efficient methodologies to collect, communicate and process position-dependent measurements, especially in situations with limit...

Bourgain’s Counterexample in the Sequential Convergence Problem for the Schrödinger Equation

Cho, C.H.; Eceizabarrena, D. (2025-05-08)

We study the problem of pointwise convergence for the Schrödinger operator on $\mathbb R^n$ along time sequences. We show that the sharp counterexample to the sequential Schrödinger maximal estimate given recently by Li, Wan...

A Unified View of Double-Weighting for Marginal Distribution Shift

Segovia, J.I; Mazuelas, S.; Liu, A. (2025-03-01)

Supervised classification traditionally assumes that training and testing samples are drawn from the same underlying distribution. However, practical scenarios are often affected by distribution shifts, such as covariate and...

Collocation-based robust variational physics-informed neural networks (CRVPINNs)

Paszyński, Maciej; Los, M.; Służalec, T.; Maczuga, P.; Vilkha, A.; Uriarte, C. (2025-09-01)

Physics-informed neural networks (PINNs) have been widely used to solve partial differential equations (PDEs) through strong residual minimization formulations. Their extension to weak scenarios via Variational PINNs (VPINNs...